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Computer Vision System Toolbox™ Release Notes
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Computer Vision System Toolbox™ Release Notes
© COPYRIGHT 2004–2015 by The MathWorks, Inc.
The software described in this document is furnished under a license agreement. The software may be used
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Contents
R2015a
3-D point cloud functions for registration, denoising,
downsampling, geometric transformation, and PLY file
reading and writing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1-2
Image search and retrieval using bag of visual words . . . . .
1-2
User-defined feature extractor for bag-of-visual-words
framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1-2
C code generation for eight functions, including
rectifyStereoImages and vision.DeployableVideoPlayer on
Mac . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1-2
Mac support for vision.DeployableVideoPlayer and To Video
Display block . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1-3
Plot camera figure in 3-D coordinate system . . . . . . . . . . . . .
1-3
Line width for insertObjectAnnotation . . . . . . . . . . . . . . . . .
1-3
Upright option for extractFeatures . . . . . . . . . . . . . . . . . . . . .
1-4
Rotate integral images in integralImage, integralKernel, and
integralFilter functions . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1-4
Performance improvements . . . . . . . . . . . . . . . . . . . . . . . . . . .
1-4
Optical flow functions and object . . . . . . . . . . . . . . . . . . . . . .
1-4
Examples for image retrieval, 3-D point cloud registration
and stitching, and code generation for depth estimation
from stereo video . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1-4
iii
R2014b
iv
Contents
Stereo camera calibration app . . . . . . . . . . . . . . . . . . . . . . . .
2-2
imageSet class for handling large collections of image files .
2-2
Bag-of-visual-words suite of functions for image category
classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2-2
Approximate nearest neighbor search method for fast feature
matching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2-2
3-D point cloud visualization function . . . . . . . . . . . . . . . . . .
2-3
3-D point cloud extraction from Kinect . . . . . . . . . . . . . . . . .
2-3
Kinect color image to depth image alignment . . . . . . . . . . . .
2-3
Point locations from stereo images using triangulation . . . .
2-3
Red-cyan anaglyph from stereo images . . . . . . . . . . . . . . . . .
2-3
Point coordinates correction for lens distortion . . . . . . . . . .
2-3
Camera projection matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2-4
Calculation of calibration standard errors . . . . . . . . . . . . . .
2-4
Live image capture in Camera Calibrator app . . . . . . . . . . .
2-4
Region of interest (ROI) copy and paste support for Training
Image Labeler app . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2-4
Non-maximal suppression of bounding boxes for object
detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2-5
Linux support for deployable video player . . . . . . . . . . . . . .
2-5
GPU support for Harris feature detection . . . . . . . . . . . . . . .
2-5
Extended language support package for optical character
recognition (OCR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2-5
Support package for OpenCV Interface . . . . . . . . . . . . . . . . .
2-5
Convert format of rectangle to a list of points . . . . . . . . . . . .
2-5
Bag-of-visual-words, stereo vision, image stitching, and
tracking examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2-5
R2014a
Stereo vision functions for rectification, disparity
calculation, scene reconstruction, and stereo camera
calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3-2
Optical character recognition (OCR) . . . . . . . . . . . . . . . . . . .
3-2
Binary Robust Invariant Scalable Keypoints (BRISK) feature
detection and extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3-2
App for labeling images for training cascade object
detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3-3
C code generation for Harris and minimum eigenvalue
corner detectors using MATLAB Coder . . . . . . . . . . . . . . .
3-3
Line width control for insertShape function and Draw
Shapes block . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3-3
Replacing vision.CameraParameters with
cameraParameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3-3
Output view modes and fill value selection added to
undistortImage function . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3-3
Generated code optimized for the matchFeatures function
and vision.ForegroundDetector System object . . . . . . . . .
3-4
v
Merging mplay viewer into implay viewer . . . . . . . . . . . . . . .
3-4
MPEG-4 and JPEG2000 file formats added to
vision.VideoFileWriter System object and To Multimedia
File block . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3-4
Region of interest (ROI) support added
to detectMSERFeatures and detectSURFFeatures
functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3-4
MATLAB code script generation added to Camera Calibrator
app . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3-4
Featured examples for text detection, OCR, 3-D
reconstruction, 3-D dense reconstruction, code generation,
and image search . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3-4
R2013b
vi
Contents
Camera intrinsic, extrinsic, and lens distortion parameter
estimation using camera calibration app . . . . . . . . . . . . . .
4-2
Camera calibration functions for checkerboard pattern
detection, camera parameter estimation, correct lens
distortion, and visualization of results . . . . . . . . . . . . . . . .
4-2
Histogram of Oriented Gradients (HOG) feature extractor .
4-2
C code generation support for 12 additional functions . . . .
4-2
System objects matlab.system.System warnings . . . . . . . . . .
4-3
Restrictions on modifying properties in System object Impl
methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4-3
R2013a
Cascade object detector training using Haar, Histogram of
Oriented Gradients (HOG), and Local Binary Pattern (LBP)
features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5-2
Fast Retina Keypoint (FREAK) algorithm for feature
extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5-2
Hamming distance method for matching features . . . . . . . .
5-2
Multicore support in matchFeatures function and
ForegroundDetector System object . . . . . . . . . . . . . . . . . . .
5-2
Functions for corner detection, geometric transformation
estimation, and text and graphics overlay, augmenting
similar System objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5-2
Error-out condition for old coordinate system . . . . . . . . . . .
5-3
Support for nonpersistent System objects . . . . . . . . . . . . . . .
5-3
New method for action when System object input size
changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5-3
Scaled double data type support for System objects . . . . . . .
5-3
Scope Snapshot display of additional scopes in Simulink
Report Generator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5-4
R2012b
Kalman filter and Hungarian algorithm for multiple object
tracking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6-2
Image and video annotation for detected or tracked
objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6-2
vii
Kanade-Lucas-Tomasi (KLT) point tracker . . . . . . . . . . . . . .
6-2
HOG-based people detector . . . . . . . . . . . . . . . . . . . . . . . . . . .
6-2
Video file reader support for H.264 codec (MPEG-4) on
Windows 7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6-2
Show matched features display . . . . . . . . . . . . . . . . . . . . . . . .
6-2
Matching methods added for match features function . . . . .
6-3
Kalman filter for tracking tutorial . . . . . . . . . . . . . . . . . . . . .
6-3
Motion-based multiple object tracking example . . . . . . . . . .
6-3
Face detection and tracking examples . . . . . . . . . . . . . . . . . .
6-3
Stereo image rectification example . . . . . . . . . . . . . . . . . . . . .
6-3
System object tunable parameter support in code
generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6-4
save and load for System objects . . . . . . . . . . . . . . . . . . . . . .
6-4
Save and restore SimState not supported for System
objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6-4
R2012a
Dependency on DSP System Toolbox and Signal Processing
Toolbox Software Removed . . . . . . . . . . . . . . . . . . . . . . . . .
Audio Output Sampling Mode Added to the From Multimedia
File Block . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Kalman Filter and Variable Selector Blocks Removed from
Library . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2-D Median and 2-D Histogram Blocks Replace Former Median
and Histogram Blocks . . . . . . . . . . . . . . . . . . . . . . . . . . . .
viii
Contents
7-2
7-2
7-2
7-2
Removed Sample-based Processing Checkbox from 2-D
Maximum, 2-D Minimum, 2-D Variance, and 2-D Standard
Deviation Blocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7-2
New Viola-Jones Cascade Object Detector . . . . . . . . . . . . . . .
7-3
New MSER Feature Detector . . . . . . . . . . . . . . . . . . . . . . . . . .
7-3
New CAMShift Histogram-Based Tracker . . . . . . . . . . . . . . .
7-3
New Integral Image Computation and Box Filtering . . . . . .
7-3
New Demo to Detect and Track a Face . . . . . . . . . . . . . . . . .
7-3
Improved MATLAB Compiler Support . . . . . . . . . . . . . . . . . .
7-3
Code Generation Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7-4
Conversion of Error and Warning Message Identifiers . . . . .
7-4
System Object Updates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Code Generation for System Objects . . . . . . . . . . . . . . . . . . .
New System Object Option on File Menu . . . . . . . . . . . . . . .
Variable-Size Input Support for System Objects . . . . . . . . . .
Data Type Support for User-Defined System Objects . . . . . . .
New Property Attribute to Define States . . . . . . . . . . . . . . . .
New Methods to Validate Properties and Get States from
System Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
matlab.system.System changed to matlab.System . . . . . . . . .
7-5
7-5
7-5
7-5
7-5
7-5
7-5
7-5
R2011b
Conventions Changed for Indexing, Spatial Coordinates, and
Representation of Geometric Transforms . . . . . . . . . . . . .
Running your Code with New Conventions . . . . . . . . . . . . . .
One-Based Indexing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Coordinate System Convention . . . . . . . . . . . . . . . . . . . . . . .
Migration to [x y] Coordinate System . . . . . . . . . . . . . . . . . .
Updated Blocks, Functions, and System Objects . . . . . . . . . .
8-2
8-2
8-2
8-2
8-4
8-4
ix
x
Contents
New SURF Feature Detection, Extraction, and Matching
Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8-11
New Disparity Function for Depth Map Calculation . . . . . .
8-12
Added Support for Additional Video File Formats for NonWindows Platforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8-12
Variable-Size Support for System Objects . . . . . . . . . . . . . .
8-12
New Demo to Retrieve Rotation and Scale of an Image Using
Automated Feature Matching . . . . . . . . . . . . . . . . . . . . . .
8-12
Apply Geometric Transformation Block Replaces Projective
Transformation Block . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8-12
Trace Boundaries Block Replaced with Trace Boundary
Block . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8-12
FFT and IFFT Support for Non-Power-of-Two Transform
Length with FFTW Library . . . . . . . . . . . . . . . . . . . . . . . .
8-13
vision.BlobAnalysis Count and Fill-Related Properties
Removed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8-13
vision.CornerDetector Count Output Removed . . . . . . . . . .
8-13
vision.LocalMaximaFinder Count Output and
CountDataType Property Removed . . . . . . . . . . . . . . . . . .
8-14
vision.GeometricTransformEstimator Default Properties
Changed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8-14
Code Generation Support . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8-14
vision.MarkerInserter and vision.ShapeInserter Properties
Not Tunable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8-15
Custom System Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8-15
System Object DataType and CustomDataType Properties
Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8-15
R2011a
Product Restructuring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
System Object Name Changes . . . . . . . . . . . . . . . . . . . . . . .
9-2
9-2
New Computer Vision Functions . . . . . . . . . . . . . . . . . . . . . . .
Extract Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Feature Matching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Uncalibrated Stereo Rectification . . . . . . . . . . . . . . . . . . . . .
Determine if Image Contains Epipole . . . . . . . . . . . . . . . . . .
Epipolar Lines for Stereo Images . . . . . . . . . . . . . . . . . . . . .
Line-to-Border Intersection Points . . . . . . . . . . . . . . . . . . . .
9-3
9-3
9-3
9-3
9-3
9-3
9-3
New Foreground Detector System Object . . . . . . . . . . . . . . .
9-3
New Tracking Cars Using Gaussian Mixture Models Demo .
9-3
Expanded To Video Display Block with Additional Video
Formats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9-4
New Printing Capability for the mplay Function and Video
Viewer Block . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9-4
Improved Display Updates for mplay Function, Video Viewer
Block and vision.VideoPlayer System Object . . . . . . . . . . .
9-4
Improved Performance of FFT Implementation with FFTW
library . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9-4
Variable Size Data Support . . . . . . . . . . . . . . . . . . . . . . . . . . .
9-4
System Object Input and Property Warnings Changed to
Errors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9-4
System Object Code Generation Support . . . . . . . . . . . . . . . .
9-5
MATLAB Compiler Support for System Objects . . . . . . . . . .
9-5
R2010a MAT Files with System Objects Load Incorrectly . .
9-5
Documentation Examples Renamed . . . . . . . . . . . . . . . . . . . .
9-5
xi
R2010b
New Estimate Fundamental Matrix Function for Describing
Epipolar Geometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10-2
New Histogram System Object Replaces Histogram2D
Object . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10-2
New System Object release Method Replaces close
Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Compatability Considerations . . . . . . . . . . . . . . . . . . . . . . .
10-2
10-2
Expanded Embedded MATLAB Support . . . . . . . . . . . . . . . .
Supported Image Processing Toolbox Functions . . . . . . . . .
Supported System objects . . . . . . . . . . . . . . . . . . . . . . . . . .
10-2
10-3
10-3
Data Type Assistant and Ability to Specify Design Minimums
and Maximums Added to More Fixed-Point Blocks . . . . .
10-3
Data Types Pane Replaces the Data Type Attributes and
Fixed-Point Panes on Fixed-Point Blocks . . . . . . . . . . . .
10-4
Enhanced Fixed-Point and Integer Data Type Support with
System Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Compatability Considerations . . . . . . . . . . . . . . . . . . . . . . .
10-4
10-4
Variable Size Data Support . . . . . . . . . . . . . . . . . . . . . . . . . .
10-4
Limitations Removed from Video and Image Processing
Blockset Multimedia Blocks and Objects . . . . . . . . . . . . .
10-4
R2010a
New System Objects Provide Video and Image Processing
Algorithms for use in MATLAB . . . . . . . . . . . . . . . . . . . . .
xii
Contents
11-2
Intel Integrated Performance Primitives Library Support
Added to 2-D Correlation, 2-D Convolution, and 2-D FIR
Filter Blocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
11-2
Variable Size Data Support . . . . . . . . . . . . . . . . . . . . . . . . . .
11-2
Expanded From and To Multimedia File Blocks with
Additional Video Formats . . . . . . . . . . . . . . . . . . . . . . . . . .
11-3
New Simulink Demos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
New Modeling a Video Processing System for an FPGA Target
Demo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
11-3
New System Object Demos . . . . . . . . . . . . . . . . . . . . . . . . . . .
New Image Rectification Demo . . . . . . . . . . . . . . . . . . . . . .
New Stereo Vision Demo . . . . . . . . . . . . . . . . . . . . . . . . . . .
New Video Stabilization Using Point Feature Matching . . .
11-3
11-3
11-3
11-4
SAD Block Obsoleted . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
11-4
11-3
xiii
R2015a
Version: 6.2
New Features
Bug Fixes
Compatibility Considerations
R2015a
3-D point cloud functions for registration, denoising, downsampling,
geometric transformation, and PLY file reading and writing
This release adds 3-D point cloud processing functions. It also adds an object for storing a
point cloud, and functions to read and write point cloud files in a PLY format.
• pctransform
• pcregrigid
• pcmerge
• pcdownsample
• pcdenoise
• pointCloud
• pcread
• pcwrite
Image search and retrieval using bag of visual words
This release adds functionality for searching large image collections. It adds the
retrieveImages, evaluateImageRetrieval, and indexImages functions, and the
invertedImageIndex object.
User-defined feature extractor for bag-of-visual-words framework
This release adds the ability to define a custom feature extractor to use with the
bagOfFeatures framework.
C code generation for eight functions, including
rectifyStereoImages and vision.DeployableVideoPlayer
on Mac
This release adds C code generation support to eight functions, one System object, and
one block. Additionally, the new optical flow functions support C code generation.
• rectifyStereoImages
• reconstructScene
• undistortImage
1-2
• triangulate
• extrinsics
• cameraMatrix
• cameraParameters
• stereoParameters
• vision.DeployableVideoPlayer
• To Video Display block on the Mac
• opticalFlow
• opticalFlowHS
• opticalFlowLK
• opticalFlowLKDoG
Mac support for vision.DeployableVideoPlayer and To Video
Display block
This release enables the vision.DeployableVideoPlayer System object and the To
Video Display block on the Mac. These players are capable of displaying high-definition
video at high frame rates.
Compatibility Considerations
The player displays frames at the rate of the video input. Setting the FrameRate
property has no effect on changing the rate of the display. The FrameRate property will
be removed in a future release.
Plot camera figure in 3-D coordinate system
This release adds the plotCamera function. The function returns a camera visualization
object to plot a camera figure in the current axes.
Line width for insertObjectAnnotation
This release introduces a LineWidth property for the insertObjectAnnotation
function. Setting this property enables you to modify the line width of inserted
annotations.
1-3
R2015a
Upright option for extractFeatures
This release introduces the Upright property for the extractFeatures function. This
property enables you to restrict extracted features to an upright orientation only.
Rotate integral images in integralImage, integralKernel, and
integralFilter functions
This release introduces rotated summed area table (RSAT) support to the
integralImage, integralKernel, and integralFilter functions.
Performance improvements
• detectCheckerboardPoints and estimateCameraParameters functions
• integralFilter function
• vision.DeployableVideoPlayer System object
• To Video Display block
Optical flow functions and object
This release adds the opticalFlowHS, opticalFlowLK, and opticalFlowLKDoG
functions. These functions enable you to compute optical flow using the Horn-Schunck
and Lucas-Kanade methods. This release also adds the opticalFlow object for storing
optical flow velocity matrices. The functions and the object support C code generation.
Examples for image retrieval, 3-D point cloud registration and stitching,
and code generation for depth estimation from stereo video
• “Image Retrieval Using Customized Bag of Features”
• “3-D Point Cloud Registration and Stitching”
• “Code Generation for Depth Estimation From Stereo Video”
1-4
R2014b
Version: 6.1
New Features
Bug Fixes
R2014b
Stereo camera calibration app
This release adds a stereo calibration app. You can use the app to calibrate a stereo
camera.Use the stereoCameraCalibrator function to invoke the app. See the Stereo
Calibration Using the Stereo Camera Calibrator App tutorial.
imageSet class for handling large collections of image files
This release adds the imageSet class for managing large collections of image files. Use
the imageSet partition method to create subsets of image sets. You can use these
subsets to provide training and validation images for classification.
Bag-of-visual-words suite of functions for image category classification
This release adds a suite of functions to support the bag-of-features workflow. The
workflow allows you to manage your image collections and partition them into training
and validation sets. It constructs a bag of visual words for use in image category
classification. The training and classification includes support for Parallel Computing
Toolbox™.
• imageSet
• bagOfFeatures
• trainImageCategoryClassifier (requires Statistics and Machine Learning Toolbox™)
• imageCategoryClassifier (requires Statistics and Machine Learning Toolbox)
Approximate nearest neighbor search method for fast feature matching
This release provides updates to the matchFeatures function. The update replaces
previous matching methods with 'Exhaustive' and 'Approximate' Nearest Neighbor
methods. It also adds the Unique match logical property to only return unique matches
from the input feature set.
As a result of this update, the following methods and properties were removed:
• 'NearestNeighborRatio', 'NearestNeighborSymmetric', and 'Threshold'
matching methods
• 'normxcorr' normalized cross-correlation metric and the 'Prenormalized'
properties
2-2
Use the following new methods to match the behavior of the removed properties.
Previous Match Method
Set New Match Method
'NearestNeighborRatio'
Set the Method property to 'Exhaustive'
and the Unique property to false.
'NearestNeighborSymmetric'
Set the Method property to
'Exhaustive', the Unique property to
true, and the MaxRatio to 1.
3-D point cloud visualization function
This release adds the showPointCloud function for plotting point clouds.
3-D point cloud extraction from Kinect
This release adds the depthToPointCloud function to convert a Kinect® depth image to a
3-D point cloud. This function requires the Image Acquisition Toolbox™.
Kinect color image to depth image alignment
This release adds the alignColorToDepth function for registering a Kinect color image to
a depth image. This function requires the Image Acquisition Toolbox.
Point locations from stereo images using triangulation
This release adds the triangulate function. You can use this function to find 3-D locations
of matching points in stereo images.
Red-cyan anaglyph from stereo images
This release adds the stereoAnaglyph function. Use this function to combine stereo
images to form an anaglyph, which can be viewed with red-blue stereo glasses.
Point coordinates correction for lens distortion
This release adds the undistortPoints function. Use this function to remove the effects of
lens distortion from individual point locations.
2-3
R2014b
Camera projection matrix
This release adds the cameraMatrix function. You can use the matrix returned by this
function to project 3-D world points in homogeneous coordinates into an image.
Calculation of calibration standard errors
This release adds the ability to return the standard errors incurred during the camera
calibration process. The estimateCameraParameters function returns the errors. You can
use the errors to evaluate the quality of the camera calibration. You can return errors for
both single and stereo camera calibration.
Live image capture in Camera Calibrator app
You can now do live camera calibration using the Camera Calibrator app. The new
Image Capture tab allows you to bring live images from USB Webcams into the app.
Previously, you had to save your images to disk and manually add them into the app.
The image capture functionality in the Camera Calibrator app allows you to:
• Capture live images from USB Webcams
• Browse the captured images
• Save acquired images
• Integrate between image acquisition and calibration
• Control camera properties, such as brightness and contrast.
Use the cameraCalibrator function to open the app. Then select Add Images > From
camera to open the Image Capture tab. Select your device, set any properties, and
define the capture settings. You can then capture images and calibrate the camera.
Region of interest (ROI) copy and paste support for Training Image
Labeler app
This release adds the ability to copy-and-paste regions of interest within the Training
Image Labeler app.
2-4
Non-maximal suppression of bounding boxes for object detection
This release adds the bboxOverlapRatio and the selectStrongestBbox functions. Use
bboxOverlapRatio to compute the overlap ratio between pairs of bounding boxes. Use
selectStrongestBbox to select the strongest bounding boxes from overlapping clusters.
Linux support for deployable video player
This release adds Linux® support for the To Video Display block and the
vision.DeployableVideoPlayer System object™. This added support includes the ability to
generate code.
GPU support for Harris feature detection
This release adds GPU acceleration for the detectHarrisFeatures function. GPU
acceleration for this function requires Parallel Computing Toolbox.
Extended language support package for optical character recognition
(OCR)
This release adds the ability to download additional language support for the ocr
function. You can use the visionSupportPackages function to download the language
support package.
Support package for OpenCV Interface
This release adds a support package to help you integrate your OpenCV C++ code into
MATLAB. It lets you build MEX files that calls OpenCV functions. You can use the
visionSupportPackages function to download the OpenCV Interface support package.
Convert format of rectangle to a list of points
This release adds the bbox2points function. You can use this function to convert a
rectangle, specified as [x, y, width, height], into a list of [x, y] points.
Bag-of-visual-words, stereo vision, image stitching, and tracking
examples
This release adds several new examples.
2-5
R2014b
• Pedestrian tracking from a moving car
• Image classification using bag-of-visual-words workflow
• Face tracking from a web cam
• Evaluate camera calibration results
• Image stitching
• Depth estimation from a stereo video
• Code generation with PackNGo
2-6
R2014a
Version: 6.0
New Features
Bug Fixes
Compatibility Considerations
R2014a
Stereo vision functions for rectification, disparity calculation, scene
reconstruction, and stereo camera calibration
This release adds a suite of stereo vision algorithms to the Computer Vision System
Toolbox™.
• rectifyStereoImages for stereo rectification.
• reconstructScene for computing dense 3-D reconstruction based on a disparity map.
• extrinsics for computing location of a calibrated camera.
• stereoParameters object for storing stereo system parameters.
• detectCheckerboardPoints extended to support stereo calibration
• disparity adds new method for semi-global block matching.
• estimateCameraParameters extended to calibrate stereo cameras.
• cameraParameters object for storing camera parameters.
• showExtrinsics extended to support stereo cameras.
• showReprojectionErrors extended to support stereo cameras.
Compatibility Considerations
This release modifies the disparity function’s default method for block matching. The new
SemiGobal default method may produce different results in code created that used the
previous BlockMatching default method. To obtain the same results, set the 'Method'
property to 'BlockMatching'.
Optical character recognition (OCR)
This release adds the ocr function and ocrText object. You can use the ocr function to
recognize text using optical character recognition. The ocrText object stores optical
character recognition results.
Binary Robust Invariant Scalable Keypoints (BRISK) feature detection and
extraction
This release adds the detectBRISKFeatures function. You can use the Binary Robust
Invariant Scalable Keypoints (BRISK) algorithm to detect multi-scale corner features.
This release also adds the BRISKPoints object to store the BRISK detection results. This
release adds BRISK descriptor to the extractFeatures.
3-2
App for labeling images for training cascade object detectors
This release adds a Training Image Labeler app. The app can be used to select regions
of interest in images for the purpose of training a classifier. You can invoke the app by
using the trainingImageLabeler function. See the Label Images for Classification Model
Training tutorial.
C code generation for Harris and minimum eigenvalue corner detectors
using MATLAB Coder
This release adds C code generation support for the detectHarrisFeatures and
detectMinEigenFeatures functions. This release also adds C code generation to the
estimateGeometricTransform function.
Line width control for insertShape function and Draw Shapes block
This release adds line thickness control to the insertShape function and the Draw
Shapes.
Replacing vision.CameraParameters with cameraParameters
This release replaces the vision.CameraParameters object with the
cameraParameters object. The new object contains identical functionality.
Compatibility Considerations
You must replace the vision.CameraParameters with cameraParameters object in
your code. If you attempt to create a vision.CameraParameters object, MATLAB®
returns an error.
Output view modes and fill value selection added to undistortImage
function
This release adds new output view modes and fill value selection to the undistortImage
function. You can control the output view size by setting the OutputView property. You
can also set the fill value with the FillValues property.
3-3
R2014a
Generated code optimized for the matchFeatures function and
vision.ForegroundDetector System object
This release provides generated code optimization for the matchFeatures function and
the vision.ForegroundDetector System object on a Windows®, Linux, Mac OS platform.
Merging mplay viewer into implay viewer
This release merges the mplay viewer function from the Computer Vision System
Toolbox into the implay function in Image Processing Toolbox™.
Compatibility Considerations
Use the implay function with functionality identical to mplay. The mplay function will be
removed in a future release.
MPEG-4 and JPEG2000 file formats added to vision.VideoFileWriter
System object and To Multimedia File block
This release adds support for writing MPEG-4 and JPEG 2000 file formats with the
vision.VideoFileWriter object and the To Multimedia File block.
Region of interest (ROI) support added to detectMSERFeatures and
detectSURFFeatures functions
This release adds region of interest (ROI) support to the detectMSERFeatures and
detectSURFFeatures functions.
MATLAB code script generation added to Camera Calibrator app
This release adds MATLAB code script generation to the Camera Calibrator app.
Featured examples for text detection, OCR, 3-D reconstruction, 3-D dense
reconstruction, code generation, and image search
This release the Computer Vision System Toolbox adds several new featured examples:
3-4
• Automatically Detect and Recognize Text in Natural Images
• Image Search using Point Features
• Recognize Text Using Optical Character Recognition (OCR)
• Code Generation for Feature Matching and Registration (updated)
• Stereo Calibration and Scene Reconstruction
• Sparse 3-D Reconstruction From Multiple Views
3-5
R2013b
Version: 5.3
New Features
Bug Fixes
Compatibility Considerations
R2013b
Camera intrinsic, extrinsic, and lens distortion parameter estimation using
camera calibration app
This release adds a camera calibration app. The app can be used to estimate camera
intrinsic and extrinsic parameters, and to compute parameters needed to remove
the effects of lens distortion from an image. You can invoke the calibrator using
the cameraCalibrator function. See the Find Camera Parameters with the Camera
Calibrator tutorial.
Camera calibration functions for checkerboard pattern detection, camera
parameter estimation, correct lens distortion, and visualization of results
This release adds a suite of functions that, when used together, provide a workflow to
calibrate a camera:
• detectCheckerboardPoints
• estimateCameraParameters
• generateCheckerboardPoints
• showExtrinsics
• showReprojectionErrors
• undistortImage
• vision.CameraParameters
Histogram of Oriented Gradients (HOG) feature extractor
This release adds the extractHOGFeatures descriptor function. The extracted features
encode local shape information from regions within an image. You can use this function
for many tasks including classification, detection, and tracking.
C code generation support for 12 additional functions
This release adds C code generation support for several Computer Vision System Toolbox
functions, classes, and System objects.
• extractHOGFeatures
• extractFeatures
4-2
• detectSURFFeatures
• disparity
• detectMSERFeatures
• detectFASTFeatures
• vision.CascadeObjectDetector
• vision.PointTracker
• vision.PeopleDetector
• MSERRegions
• cornerPoints
• SURFPoints
System objects matlab.system.System warnings
The System object base class, matlab.system.System has been replaced by
matlab.System. If you use matlab.system.System when defining a new System
object, a warning message results.
Compatibility Considerations
Change all instances of matlab.system.System in your System objects code to
matlab.System.
Restrictions on modifying properties in System object Impl methods
When defining a new System object, certain restrictions affect your ability to modify a
property.
You cannot use any of the following methods to modify the properties of an object:
• cloneImpl
• getDiscreteStateImpl
• getDiscreteStateSpecificationImpl
• getNumInputsImpl
• getNumOutputsImpl
• getOutputDataTypeImpl
4-3
R2013b
• getOutputSizeImpl
• isInputDirectFeedthroughImpl
• isOutputComplexImpl
• isOutputFixedSizeImpl
• validateInputsImpl
• validatePropertiesImpl
This restriction is required by code generation, which assumes that these methods do not
change any property values. These methods are validation and querying methods that
are expected to be constant and should not impact the algorithm behavior.
Also, if either of the following conditions exist:
• You plan to generate code for the object
• The object will be used in the MATLAB System block
you cannot modify tunable properties for any of the following runtime methods:
• outputImpl
• processTunedPropertiesImpl
• resetImpl
• setupImpl
• stepImpl
• updateImpl
This restriction prevents tunable parameter updates within the object from interfering
with updates from outside the generated code. Tunable parameters can only be changed
from outside the generated code.
Compatibility Considerations
If any of your class definition files contain code that changes a property in one of the
above Impl methods, move that property code into an allowable Impl method. Refer to
the System object Impl method reference pages for more information.
4-4
R2013a
Version: 5.2
New Features
Bug Fixes
Compatibility Considerations
R2013a
Cascade object detector training using Haar, Histogram of Oriented
Gradients (HOG), and Local Binary Pattern (LBP) features
This release adds the trainCascadeObjectDetector function for Haar, Histogram of
Oriented Gradients (HOG), and Local Binary Pattern (LBP) features. The function
creates a custom classification model to use with the vision.CascadeObjectDetector
cascade object detector.
Fast Retina Keypoint (FREAK) algorithm for feature extraction
This release adds the Fast Retina Keypoint (FREAK) descriptor algorithm to the
extractFeatures function. This function now supports the FREAK method for descriptor
extraction.
Hamming distance method for matching features
This release adds the Hamming distance method to the matchFeatures function in
support of binary features produced by descriptors such as the FREAK method for
extraction. It also adds the new binaryFeatures object, which is an output of the
extractFeatures function and serves as an input to the matchFeatures function.
Multicore support in matchFeatures function and
ForegroundDetector System object
This release brings multicore performance improvements for the matchFeatures function
and the vision.ForegroundDetector detector.
Functions for corner detection, geometric transformation estimation, and
text and graphics overlay, augmenting similar System objects
This release adds several new functions. For corner detection, the new
detectHarrisFeatures, detectMinEigenFeatures, and detectFASTFeatures functions.
The insertText, insertMarker, and insertShape functions for inserting text, markers,
and shapes into images and video. Lastly, the estimateGeometricTransform function for
estimating a geometric transform from putatively matched point pairs.
5-2
Error-out condition for old coordinate system
This release ends support for the row-column coordinate system for the Computer Vision
System Toolbox algorithms. All blocks are replaced with blocks using [x y] coordinates,
and all functions and System objects are updated to use the one-based [x y] convention.
Using any MATLAB or Simulink® related algorithms will error out when using RC-based
functions or blocks.
Compatibility Considerations
Conventions for indexing, spatial coordinates, and representation of geometric
transforms were changed in R2011b to provide improved interoperability with the Image
Processing Toolbox product. Beginning in this release, all Computer Vision System
Toolbox blocks, functions, classes, and System objects will only operate in the [x y]
coordinate system. Blocks affected by the [x y] coordinate system should be replaced with
blocks of the same name from the Vision library. Adjust your models, code, and data as
necessary.
For extended details on the coordinate system change, see “Conventions Changed for
Indexing, Spatial Coordinates, and Representation of Geometric Transforms” on page
8-2 R2011b Release Notes.
Support for nonpersistent System objects
You can now generate code for local variables that contain references to System objects.
In previous releases, you could not generate code for these objects unless they were
assigned to persistent variables.
New method for action when System object input size changes
The new processInputSizeChangeImpl method allows you to specify actions to take
when an input to a System object you defined changes size. If an input changes size after
the first call to step, the actions defined in processInputSizeChangeImpl occur when
step is next called on that object.
Scaled double data type support for System objects
System objects now support scaled double data types.
5-3
R2013a
Scope Snapshot display of additional scopes in Simulink Report
Generator
Using Simulink Report Generator™ software, you can include snapshots of the display
produced by a Scope block in a generated report. The Scope Snapshot component, which
inserts images of the Simulink Scope block and XY Graph block, now supports the Video
Viewer block in Computer Vision System Toolbox software.
Note: This feature requires that you have a license for the Simulink Report Generator
product.
For more information, see the Simulink Report Generator product documentation.
5-4
R2012b
Version: 5.1
New Features
Bug Fixes
Compatibility Considerations
R2012b
Kalman filter and Hungarian algorithm for multiple object tracking
The vision.KalmanFilter object is designed for object tracking. You can use it to predict
an object's future location, to reduce noise in the detected location, or to help associate
multiple objects with their corresponding tracks. The configureKalmanFilter function
helps you to set up the Kalman filter object.
The assignDetectionsToTracks function assigns detections to tracks in the context of
multiple object tracking using the James Munkres' variant of the Hungarian assignment
algorithm. The function also determines which tracks are missing, and which detections
should begin a new track.
Image and video annotation for detected or tracked objects
The insertObjectAnnotation function inserts labels and corresponding circles or
rectangles into an image or video to easily display tracked objects. You can use it with
either a grayscale or true color image input.
Kanade-Lucas-Tomasi (KLT) point tracker
The vision.PointTracker object tracks a set of points using the Kanade-Lucas-Tomasi
(KLT), feature tracking algorithm. You can use the point tracker for video stabilization,
camera motion estimation, and object tracking.
HOG-based people detector
The vision.PeopleDetector object detects people in an input image using the Histogram
of Oriented Gradient (HOG) features and a trained Support Vector Machine (SVM)
classifier. The object detects unoccluded people in an upright position.
Video file reader support for H.264 codec (MPEG-4) on Windows 7
This release adds H.264 codec (MPEG-4) video formats for Windows 7 operating systems.
Show matched features display
The showMatchedFeatures function displays corresponding feature points. It displays
a falsecolor overlay of two images with a color-coded plot of the corresponding points
connected by a line.
6-2
Matching methods added for match features function
This release enhances the matchFeatures function for applications in computing the
fundamental matrix, stereo vision, registration, and object detection. It provides three
different matching methods: simple threshold match, unique matches, and unambiguous
matches.
Compatibility Considerations
The new implementation of matchFeatures uses different default value for the
method parameter. If you need the same results as those produced by the previous
implementation, set the Method parameter with syntax:
matchFeatures(FEATURES1, FEATURES2, 'Method', 'NearestNeighbor_old', ...).
Kalman filter for tracking tutorial
The Kalman filter is a popular tool for object tracking. The Using Kalman Filter
for Object Tracking example helps you to understand how to setup and use the
vision.KalmanFilter object and the configureKalmanFilter function to track objects.
Motion-based multiple object tracking example
The Motion-Based Multiple Object Tracking example shows you how to perform
automatic detection and motion-based tracking of moving objects in a video from a
stationary camera.
Face detection and tracking examples
The Face Detection and Tracking example shows you how to automatically detect and a
track a face. The Face Detection and Tracking Using the KLT Algorithm example uses
the Kanade-Lucas-Tomasi (KLT) algorithm and shows you how to automatically detect a
face and track it using a set of feature points.
Stereo image rectification example
This release enhances the Stereo Image Rectification example. It uses SURF feature
detection with the estimateFundamentalMatrix, estimateUncalibratedRectification, and
6-3
R2012b
detectSURFFeatures functions to compute the rectification of two uncalibrated images,
where the camera intrinsics are unknown.
System object tunable parameter support in code generation
You can change tunable properties in user-defined System objects at any time, regardless
of whether the object is locked. For System objects predefined in the software, the object
must be locked. In previous releases, you could tune System object properties only for a
limited number of predefined System objects in generated code.
save and load for System objects
You can use the save method to save System objects to a MAT file. If the object is locked,
its state information is saved, also. You can recall and use those saved objects with the
load method.
You can also create your own save and load methods for a System object you create.
To do so, use the saveObjectImpl and loadObjectImpl, respectively, in your class
definition file.
Save and restore SimState not supported for System objects
The Save and Restore Simulation State as SimState option is no longer supported for
any System object in a MATLAB Function block. This option was removed because
it prevented parameter tunability for System objects, which is important in code
generation.
Compatibility Considerations
If you need to save and restore simulation states, you may be able to use a corresponding
Simulink block, instead of a System object.
6-4
R2012a
Version: 5.0
New Features
Bug Fixes
Compatibility Considerations
R2012a
Dependency on DSP System Toolbox and Signal Processing Toolbox
Software Removed
The DSP System Toolbox™ and Signal Processing Toolbox™ software are no longer
required products for using Computer Vision System Toolbox software. As a result, a few
blocks have been modified or removed.
Audio Output Sampling Mode Added to the From Multimedia File Block
The From Multimedia File block now includes a new parameter, which allows you to
select frame- or sample-based audio output. If you do not have a DSP System Toolbox
license and you set this parameter for frame-based processing, your model will return an
error. The Computer Vision System Toolbox software uses only sample-based processing.
Kalman Filter and Variable Selector Blocks Removed from Library
This release removes the Kalman Filter and Variable Selector Blocks from the Computer
Vision System Toolbox block library.
Compatibility Considerations
To use these blocks or to run a model containing these blocks, you must have a DSP
System Toolbox license.
2-D Median and 2-D Histogram Blocks Replace Former Median and Histogram Blocks
The Median and Histogram blocks have been removed. You can replace these blocks with
the 2-D Median and the 2-D Histogram blocks.
Compatibility Considerations
Replace these blocks in your models with the new 2-D blocks from the Computer Vision
System Toolbox library.
Removed Sample-based Processing Checkbox from 2-D Maximum, 2-D Minimum, 2-D
Variance, and 2-D Standard Deviation Blocks
This release removes the Treat sample-based row input as a column checkbox from
the 2-D Maximum, 2-D Minimum, 2-D Variance, and 2-D Standard Deviation statistics
blocks.
7-2
Compatibility Considerations
Modify your code accordingly.
New Viola-Jones Cascade Object Detector
The vision.CascadeObjectDetector System object uses the Viola-Jones algorithm to detect
objects in an image. This detector includes Haar-like features and a cascade of classifiers.
The cascade object detector is pretrained to detect faces, noses and other objects.
New MSER Feature Detector
The detectMSERFeatures function detects maximally stable extremal regions (MSER)
features in a grayscale image. You can use the MSERRegions object, returned by the
function, to manipulate and plot MSER features.
New CAMShift Histogram-Based Tracker
The vision.HistogramBasedTracker System object uses the continuously adaptive mean
shift (CAMShift) algorithm for tracking objects. It uses the histogram of pixel values to
identify the object.
New Integral Image Computation and Box Filtering
The integralKernel object with the integralImage and integralFilter functions use
integral images for filtering an image with box filters. The speed of the filtering operation
is independent of the filter size, making it ideally suited for fast analysis of images at
different scales.
New Demo to Detect and Track a Face
This release provides a new demo, Face Detection and Tracking. This example shows you
how to develop a simple face tracking system by detecting a face, identifying its facial
features, and tracking it.
Improved MATLAB Compiler Support
MATLAB Compiler™ now supports detectSURFFeatures and disparity functions.
7-3
R2012a
Code Generation Support
The vision.HistogramBasedTracker and vision.CornerDetector System objects now
support code generation. See About MATLAB Coder for more information about code
generation.
Conversion of Error and Warning Message Identifiers
This release changes error and warning message identifiers.
Compatibility Considerations
If you have scripts or functions using message identifiers that have changed, you must
update the code to use the new identifiers. Typically, you use message identifiers to
turn off specific warning messages. You can also use them in code that uses a try/catch
statement and performs an action based on a specific error identifier.
For example, the <'XXXXX:old:ID'> identifier has changed to <'new:similar:ID'>. If your
code checks for <'XXXXX:old:ID'>, you must update it to check for <'new:similar:ID'>
instead.
To determine the identifier for a warning, run the following command just after you see
the warning:
[MSG,MSGID] = lastwarn;
This command saves the message identifier to the variable MSGID.
To determine the identifier for an error that appears at the MATLAB prompt, run the
following command just after you see the error.
exception = MException.last;
MSGID = exception.identifier;
Note: Warning messages indicate a potential issue with your code. While you can turn off
a warning, a suggested alternative is to change your code without producing a warning.
7-4
System Object Updates
Code Generation for System Objects
System objects defined by users now support C code generation. To generate code, you
must have the MATLAB Coder™ product.
New System Object Option on File Menu
The File menu on the MATLAB desktop now includes a New > System object menu
item. This option opens a System object class template, which you can use to define a
System object class.
Variable-Size Input Support for System Objects
System objects that you define now support inputs that change size at runtime.
Data Type Support for User-Defined System Objects
System objects that you define now support all MATLAB data types as inputs and
outputs.
New Property Attribute to Define States
R2012a adds the new DiscreteState attribute for properties in your System object
class definition file. Discrete states are values calculated during one step of an object’s
algorithm that are needed during future steps.
New Methods to Validate Properties and Get States from System Objects
The following methods have been added:
• validateProperties – Checks that the System object is in a valid configuration.
This applies only to objects that have a defined validatePropertiesImpl method
• getDiscreteState – Returns a struct containing a System object’s properties that
have the DiscreteState attribute
matlab.system.System changed to matlab.System
The base System object class name has changed from matlab.system.System to
matlab.System.
7-5
R2012a
Compatibility Considerations
The previous matlab.system.System class will remain valid for existing System
objects. When you define new System objects, your class file should inherit from the
matlab.System class.
7-6
R2011b
Version: 4.1
New Features
Bug Fixes
Compatibility Considerations
R2011b
Conventions Changed for Indexing, Spatial Coordinates, and
Representation of Geometric Transforms
Conventions for indexing, spatial coordinates, and representation of geometric
transforms have been changed to provide improved interoperability with the Image
Processing Toolbox product.
Running your Code with New Conventions
How to run code
Solution
Written with R2011b
or later
(New User)
You can safely ignore the warning, and turn it off. Your code
will use the one-based [x y] coordinate system.
Written prior to
R2011b
To run your pre-R2011b code using the zero-based [row column]
conventions, invoke vision.setCoordinateSystem('RC') command
prior to running your code.
To turn the warning off, place the following command in your
startup.m file:
warning('off','vision:transition:usesOldCoordinates')
Support for the pre-R2011b coordinate system will be removed
in a future release. You should update your code to use R2011b
coordinate system conventions.
To turn the warning off, place the following command in your
startup.m file:
warning('off','vision:transition:usesOldCoordinates')
One-Based Indexing
The change from zero-based to one-based indexing simplifies the ability to blend Image
Processing Toolbox functionality with Computer Vision System Toolbox algorithms and
visualization functions.
Coordinate System Convention
Image locations in the Computer Vision System Toolbox are now expressed in [x y]
coordinates, not in [row column]. The orientation of matrices containing image locations
has changed. In previous releases, the orientation was a 2-by-N matrix of zero-based
[row column] point coordinates. Effective in R2011b, the orientation is an M-by-2 matrix
8-2
of one-based [x y] point coordinates. Rectangular ROI representation changed from [r c
height width] to [x y width height].
Example: Convert a point represented in the [r c] coordinate system to a point
in the [x y] coordinate system
Convert your data to be consistent with MATLAB and the Image Processing Toolbox
coordinate systems by switching the order indexing and adding 1 to each dimension. The
row index dimension corresponds to the y index, and the column index corresponds to the
x index. The following figure shows the equivalent row-column and x-y coordinates for a
pixel location in an image.
The following MATLAB code converts point coordinates from an [r c] coordinate system
to the [x y] coordinate system:
ptsRC = [2 0; 3 5]
% Two RC points at [2 3] and [0 5]
ptsXY = fliplr(ptsRC'+1) % RC points converted to XY
Example: Convert a bounding box represented in the [r c] coordinate system to
the [x y] coordinate system
% Two bounding boxes represented as [r c height width]
% First box is [2 3 10 5] and the second box is[0 5 15 10]
bboxRC = [2 0; 3 5; 10 15; 5 10]
% Convert the boxes to XY coordinate system format [x y width heigth]
bboxXY = [fliplr(bboxRC(1:2,:)'+1) fliplr(bboxRC(3:4,:)')]
8-3
R2011b
Example: Convert an affine geometric transformation matrix represented in
the [r c] coordinate system to the [x y] coordinate system
% Transformation matrix [h1 h2 h3; h4 h5 h6] represented in RC coordinates
tformRC = [5 2 3; 7 8 13]
% Transformation matrix [h5 h2; h4 h1; h6 h3] represented in XY coordinates
temp = rot90(tformRC,3);
tformXY = [flipud(temp(1:2,:)); temp(3,:)]
Note: You cannot use this code to remap a projective transformation matrix. You must
derive the tformXY matrix from your data.
See Expressing Image Locations for an explanation of pixel and spatial coordinate
systems.
Migration to [x y] Coordinate System
By default, all Computer Vision System Toolbox blocks, functions, and System objects
are set to operate in the [x y] coordinate system. Use the vision.setCoordinateSystem
and vision.getCoordinateSystem functions to help you migrate your code, by enabling
you to revert to the previous coordinate system until you can update your code. Use
vision.setCoordinateSystem('RC') call to set the coordinate system back to the
zero-based [r c] conventions .
For Simulink users, blocks affected by the [x y] coordinate system should be replaced
with blocks of the same name from the Vision library. Old blocks are marked with a red
“Replace” badge. The following figure shows the Hough Lines block, as it would appear
with the Replace badge, indicating that it should be replaced with the Hough Lines block
from the R2011b version.
Support for the pre-R2011b coordinate system will be removed in a future release.
Updated Blocks, Functions, and System Objects
The following table provides specifics for the functions, System objects, and blocks that
were affected by this update:
8-4
Functions
Description of Update
Prior to R2011b
R2011b
epipolarLine
The output A,B,C
line parameters were
changed to work
with [x y] one-based
coordinates.
A*row + B*col + C
A*x + B*y + C
Accepts Fundamental
matrix in [x y] format.
estimateFundamentalMatrix
Adjusted to format of
fundamental matrix.
Modified to work
with points expressed
in [x y] one-based
coordinates.
[r;c] 2-by-N zero-based [x y] M-by-2 one-based
points.
points.
Fundamental matrix
formatted points
for [r;c] zero-based
coordinates.
Fundamental matrix
formatted to work
with [x y] one-based
coordinates.
estimateUncalibratedRectification
Fundamental matrix,
matched points, and
output projective
transformation
matrices provided in
new format.
Fundamental matrix
formatted only for
zero-based [r;c]
coordinate system
Fundamental matrix
formatted for one-based
[x y] coordinate system.
extractFeatures
Converted to accept [x
y] coordinates
[r;c] 2-by-N zero-based [x y] M-by-2 one-based
points.
points.
isEpipoleInImage
Adjusted Fundamental
matrix format.
Converted to [x y]
coordinates.
Fundamental matrix
formatted only for
zero-based [r;c]
coordinate system.
Fundamental matrix
formatted only for onebased, [x y] coordinate
system.
lineToBorderPoints
The input A,B,C line
parameters were
changed to work with [x
y] coordinates.
A*row + B*col + C,
where A,B, and C are
represented in a 3by-N matrix of [r;c]
zero-based points.
A*x + B*y + C,
where A,B, and C are
represented in an Mby-3 matrix of [x y] onebased points.
[r;c] 2-by-N zero-based [x y] M-by-2 one-based
points.
points.
8-5
R2011b
Functions
matchFeatures
Description of Update
Prior to R2011b
R2011b
Output intersection
points converted to [x
y] one-based coordinate
system.
The function returned
the intersection points
in an 4-by-M matrix.
format of [r1;c1;r2;c2]
zero-based coordinate
system.
The function returns the
intersection points in an
M-by-4 matrix of format
of [x1, y1, x2, y2] onebased coordinate system.
Converted the Index
Pairs matrix to match
orientation of the
POINTS with [x y] onebased coordinates.
The function returns
the output Index Pairs
in a 2-by-M [r c] zerobased format.
The function returns the
output Index Pairs in a
M-by-2 [x y] one-based
format.
Changed orientation of Input feature vectors
input feature vectors.
stored in columns.
System Objects
8-6
Description of Update
Prior to R2011b
Input feature vectors
stored in rows.
R2011b
vision.AlphaBlender Converted Location Location format
property to take [x y] in [r;c] zero-based
coordinate location. coordinates.
Location format
in [x y] one-based
coordinates.
vision.BlobAnalysis
Centroid format
in 2-by-M [r1 r2;
c1 c2] zero-based
coordinates.
Centroid format in
M-by-2 of format [x1
y1 x2 y2] one-based
coordinates.
Bounding Box
format in 4-by-N
zero-based matrix
[r;c;height;width].
Bounding Box format
in M-by-4 one-based
matrix [x y width
height].
Centroid and
Bounding Box
formats converted
to [x y] coordinate
system.
vision.BoundaryTracerConverted to accept 2-by-N matrix of
and output [x y] one- [r c] zero-based
based points.
coordinates.
M-by-2 matrix of
[x y] one-based
coordinates.
vision.CornerDetector Corner locations
converted to [x y]
coordinate system.
Corner locations in
an M-by-2 one-based
[x y] coordinates.
Corner location
in a 2-by-N set of
[r c] zero-based
coordinates.
System Objects
Description of Update
Prior to R2011b
R2011b
vision.GeometricScalerConverted ROI input Shape in [r c height
to [x y] coordinate
width] zero-based
one-based system.
matrix.
Shape in [x y width
height] one-based
matrix.
vision.GeometricTransformer
Converted
transformation
matrix format to
support changed
ROI [x y] one-based
coordinate system
format.
Transformation
matrix formatted
only for zero-based
[r;c] coordinate
system.
Takes one-based, [x
y] coordinate format
for Transformation
matrix.
ROI format in
[r;c;height;width]
zero-based format.
ROI format in [x y
width height] onebased format.
vision.GeometricTransformEstimator
Converted
formatting for input
points.
Input points: [r1
r2;c1 c2].
Input points: [x1 y1;
x2 y2].
Converted
transformation
matrix to [x y] onebased coordinate
system.
Transformation
matrix formatted
only for zero-based
[r;c] coordinate
system.
Transformation
matrix format
matches Image
Processing Toolbox
format.
Converted format
for lines to [x y] onebased coordinate
system.
Output: [r11 r21;
Output: [x11 y11
c11 c21; r12 r22; c12 x12 y12; x21 y21 x22
c22].
y22].
vision.HoughLines
Size of output in a
4-by-N zero-based
matrix.
Size of the output
in M-by-4 one-based
matrix.
vision.LocalMaximaFinder
Converted format for 2-by-N zero-based [r M-by-2 one-based [x
Maxima locations
c] coordinates.
y] coordinates.
vision.MarkerInserter Converted format for 2-by-N zero-based [r M-by-2, one-based [x
locations.
c] coordinates.
y] coordinates.
vision.Maximum
Converted formats
vision.Mean
for line and rectangle
vision.Minimum
ROIs.
vision.StandardDeviation
vision.Variance
Line: [r1 c1 r2 c2 r3
c3].
Line: [x1 y1 x2 y2 x3
y3].
Rectangle: [r c height Rectangle: [x y width
width].
height].
8-7
R2011b
System Objects
Description of Update
vision.ShapeInserter Converted format
for rectangles, lines,
polygons, and circles
to [x y] one-based
format.
Input image
intensity values
converted to [x y]
one-based format.
vision.TemplateMatcher
Converted Location
and ROI format
to [x y] one-based
coordinate system.
vision.TextInserter
Prior to R2011b
R2011b
Rectangle: [r; c;
height; width] zerobased format.
Rectangle: [x y width
height] one-based
format.
Line: [r1 c1 r2 c2]
zero-based format.
Line: [x1 y1 x2 y2]
one-based format.
Polygon: 4-by-M
zero-based matrix.
Polygon: M-by-4 onebased matrix.
Circle: [r c radius]
zero-based format.
Circle: [x y radius]
one-based format.
N-by-M and N-by-M- M-by-N and M-by-Nby-P [r c] zero-based by-P [x y] one-based
format.
format.
Location output: [r; Location output: [x y]
c] zero-based format. one-based format.
ROI: [r c height
width] zero-based
format.
Converted location
2-by-N zero-based
and color orientation. [r;c] locations.
numColorPlanesby-N zero-based
format.
8-8
ROI processing: [x y
width height] onebased format.
M-by-2 [x y] onebased locations.
Mby-numColorPlanes
one-based format.
Blocks
Description of Update
Prior to R2011b
R2011b
Apply Geometric
Transformation
Converted
Transformation
matrix format to
support changed
ROI [x y] one-based
coordinate system
format.
Transformation
matrix formatted
only for zero-based
[r;c] coordinate
system.
Takes one-based, [x
y] coordinate format
for Transformation
matrix.
ROI format in
[r;c;height;width]
zero-based format.
ROI format in [x y
width height] onebased format.
Blocks
Description of Update
Prior to R2011b
R2011b
Blob Analysis
Centroid and
Bounding Box
formats converted
to [x y] coordinate
system.
Centroid format
in 2-by-M [r1 r2;
c1 c2] zero-based
coordinates.
Centroid format in
M-by-2 of format [x1
y1 x2 y2] one-based
coordinates.
Bounding Box
format in 4-by-N
zero-based matrix
[r;c;height;width].
Bounding Box format
in M-by-4 one-based
matrix [x y width
height].
Compositing
Converted Location
property to takes
[x y] coordinate
location.
Location format
in [r;c] zero-based
coordinates.
Location format
in [x y] one-based
coordinates.
Corner Detection
Corner locations
converted to [x y]
coordinate system.
Corner location
in a 2-by-N set of
[r c] zero-based
coordinates.
Corner locations in an
M-by-2 one-based [x
y] coordinates.
Draw Markers
Converted format for 2-by-N zero-based [r M-by-2, one-based [x
locations.
c] coordinates.
y] coordinates.
Draw Shapes
Converted format
for rectangles, lines,
polygons, and circles
to [x y] one-based
format.
Estimate Geometric Converted
Transformation
formatting for input
points.
Rectangle: [r; c;
height; width] zerobased format.
Rectangle: [x y width
height] one-based
format.
Line: [r1 c1 r2 c2]
zero-based format.
Line: [x1 y1 x2 y2]
one-based format.
Polygon: 4-by-M
zero-based matrix.
Polygon: M-by-4 onebased matrix.
Circle: [r c radius]
zero-based format
Circle: [x y radius]
one-based format.
Input points: [r1
r2;c1 c2].
Input points: [x1 y1;
x2 y2].
8-9
R2011b
Blocks
Description of Update
Prior to R2011b
R2011b
Converted
Transformation
matrix to [x y] onebased coordinate
system.
Transformation:
Transformation
T=[t22 t12 t32; t21
matrix format
t11 t31; t23 t13 t33]. matches Image
Processing Toolbox
format.
Find Local Maxima Converted format for 2-by-N zero-based [r M-by-2 one-based [x
Maxima locations
c] coordinates.
y] coordinates.
Hough Lines
Converted format
for lines to [x y] onebased coordinate
system.
Template Matching Converted Location
and ROI format
to [x y] one-based
coordinate system.
nsert Text
8-10
Output: [r11 r21;
Output: [x11 y11 x12
c11 c21; r12 r22; c12 y12; x21 y21 x22 y22].
c22].
Size of output in a
4-by-N zero-based
matrix.
Size of the output
in M-by-4 one-based
matrix.
Location output: [r; Location output: [x y]
c] zero-based format. one-based format.
ROI: [r c height
width] zero-based
format.
Converted location
2-by-N zero-based
and color orientation. [r;c] locations.
numColorPlanesby-N zero-based
format.
ROI processing: [x y
width height] onebased format.
M-by-2 [x y] onebased locations.
Mby-numColorPlanes
one-based format.
2-D Maximum2D Mean2-D
Minimum2D Standard
Deviation2-D
Variance
Converted formats
Line: [r1 c1 r2 c2 r3
for line and rectangle c3].
ROIs.
Rectangle: [r c height
width].
Line: [x1 y1 x2 y2 x3
y3].
Resize
Converted ROI input Shape in [r c height
to [x y] coordinate
width] zero-based
one-based system.
matrix.
Shape in [x y width
height] one-based
matrix.
Rectangle: [x y width
height].
Blocks
Description of Update
Prior to R2011b
Trace Boundary
Converted to accept 2-by-N matrix of
and output [x y] one- [r c] zero-based
based points.
coordinates.
R2011b
M-by-2 matrix of
[x y] one-based
coordinates.
Compatibility Considerations
Blocks affected by the [x y] coordinate system should be replaced with blocks of the same
name from the Vision library. Old blocks are marked with a red “Replace” badge. The
following figure shows a block which was affected by the coordinate system change:
Adjust your model and data as necessary. All functions and System objects are updated
to use the one-based [x y] convention.
By default, all Computer Vision System Toolbox blocks, functions, and System objects are
set to operate in the [x y] coordinate system. Use the vision.setCoordinateSystem
and vision.getCoordinateSystem functions to help migrate your code
containing System objects and functions to the [x y] coordinate system. Use
vision.setCoordinateSystem('RC') call to temporarily set the coordinate system to
old conventions.
When you invoke an affected block, object, or function, a one time, per MATLAB session,
warning appears.
See the section, Expressing Image Locations for a description of the coordinate systems
now used by the Computer Vision System Toolbox product.
New SURF Feature Detection, Extraction, and Matching Functions
This release introduces a new Speeded Up Robust Features (SURF) detector
with functions supporting interest feature detection, extraction and matching.
The detectSURFFeatures function returns information about SURF features
detected in a grayscale image. You can use the SURFPoints object returned by the
detectSURFFeatures function to manipulate and plot SURF features.
8-11
R2011b
New Disparity Function for Depth Map Calculation
The new disparity function provides the disparity map between a pair of stereo images.
You can use the disparity function to find relative depth of the scene for tasks such as,
segmentation, robot navigation, or 3-D scene reconstruction.
Added Support for Additional Video File Formats for Non-Windows
Platforms
The From Multimedia File block and the vision.VideoFileReader now support many
compressed video file formats on Linux and Macintosh OS X platforms.
Variable-Size Support for System Objects
Computer Vision System Toolbox System objects support inputs that change their size at
run time.
New Demo to Retrieve Rotation and Scale of an Image Using Automated
Feature Matching
This release provides a new demo, Finding the Rotation and Scale of an Image
Using Automated Feature Matching. This demo shows you how to use the
vision.GeometricTransformEstimator System object and the new detectSURFFeatures
function to find the rotation angle and scale factor of a distorted image.
Apply Geometric Transformation Block Replaces Projective Transformation
Block
The Projective Transformation block will be removed in a future release. It is
recommended that you replace this block with the combination of Apply Geometric
Transformation and the Estimate Geometric Transformation blocks to apply projective or
affine transform to an image.
Trace Boundaries Block Replaced with Trace Boundary Block
This release provides a replacement block for the Trace Boundaries block. The Trace
Boundary block now returns variable size data. See Working with Variable-Size Signals
for more information about variable size data.
8-12
Note: Unlike the Trace Boundaries block, the new Trace Boundary block only traces a
single boundary.
The Trace Boundaries block will be removed in a future release.
Compatibility Considerations
The new Trace Boundary block no longer provides the Count output port that the
older Trace Boundaries block provided. Instead, the new Trace Boundary block and the
corresponding vision.BoundaryTracer System object now return variable size data.
FFT and IFFT Support for Non-Power-of-Two Transform Length with FFTW
Library
The 2-D FFT and 2-D IFFT blocks and the vision.IFFT and vision.FFT System objects
include the use of the FFTW library. The blocks and objects now support non-power-oftwo transform lengths.
vision.BlobAnalysis Count and Fill-Related Properties Removed
The blob analysis System object now supports variable-size outputs. Therefore, the
Count output, and the NumBlobsOutputPort, FillEmptySpaces, and FillValues
properties related to fixed-size outputs, were removed from the object.
Compatibility Considerations
Remove these properties from your code, and update accordingly. If you require an
explicit blob count, call size on one of the object’s outputs, such as AREA.
vision.CornerDetector Count Output Removed
The corner detector System object now supports variable-size outputs. Therefore, the
Count output related to fixed-size outputs, were removed from the object.
Compatibility Considerations
Update your code accordingly. If you require an explicit count, call size on the object
METRIC output.
8-13
R2011b
vision.LocalMaximaFinder Count Output and CountDataType Property
Removed
The local maxima finder System object now supports variable-size outputs. Therefore,
the Count output, and the CountDataType property related to fixed-size outputs, were
removed from the object.
Compatibility Considerations
Remove the property from your code, and update accordingly.
vision.GeometricTransformEstimator Default Properties Changed
The following default property values for the vision.GeometricTransformEstimator
System object have been changed to provide more reliable outputs.
Property
Default Value
Transform
From
To
Projective
Affine
AlgebraicDistanceThreshold1.5
2.5
PixelDistanceThreshold
1.5
2.5
NumRandomSamplings
100
500
MaximumRandomSamples
200
1000
Compatibility Considerations
The effect of these changes make the object’s default-value computations more reliable.
If your code relies on the previous default values, you might need to update the affected
property values.
Code Generation Support
The vision.IFFT System object now supports code generation. See About MATLAB Coder
for more information about code generation.
8-14
vision.MarkerInserter and vision.ShapeInserter Properties Not Tunable
The following vision.MarkerInserter and vision.ShapeInserter properties are
now nontunable:
• FillColor
• BorderColor
When objects are locked (for instance, after calling the step method), you cannot change
any nontunable property values.
Compatibility Considerations
Review any code that changes any vision.MarkerInserter or
vision.ShapeInserter property value after calling the step method. You should
update the code to use property values that do not change.
Custom System Objects
You can now create custom System objects in MATLAB. This capability allows you to
define your own System objects for time-based and data-driven algorithms, I/O, and
visualizations. The System object API provides a set of implementation and service
methods that you incorporate into your code to implement your algorithm. See Define
New System Objects in the DSP System Toolbox documentation for more information.
System Object DataType and CustomDataType Properties Changes
When you set a System object, fixed-point <xxx>DataType property to ‘Custom’, it
activates a dependent Custom<xxx>DataType property. If you set that dependent
Custom<xxx>DataType property before setting its <xxx>DataType property, a warning
message displays. <xxx> differs for each object.
Compatibility Considerations
Previously, setting the dependent Custom<xxx>DataType property would automatically
change its <xxx>DataType property to ‘Custom’. If you have code that sets the
dependent property first, avoid warnings by updating your code. Set the <xxx>DataType
property to ‘Custom’ before setting its Custom<xxx>DataType property.
8-15
R2011b
Note: If you have a Custom<xxx>DataType in your code, but do not explicitly update
your code to change <xxx>DataType to ‘Custom’, you may see different numerical
output.
8-16
R2011a
Version: 4.0
New Features
Bug Fixes
Compatibility Considerations
R2011a
Product Restructuring
The Video and Image Processing Blockset has been renamed to Computer Vision System
Toolbox. This product restructuring reflects the broad expansion of computer vision
capabilities for the MATLAB and Simulink environments. The Computer Vision System
Toolbox software requires the Image Processing Toolbox and DSP System Toolbox
software.
You can access archived documentation for the Video and Image Processing Blockset™
products on the MathWorks website.
System Object Name Changes
Package Name Change
The System object package name has changed from video to vision. For example,
video.BlobAnalysis is now vision.BlobAnalysis.
Object Name Changes
The 2D System object names have changed. They no longer have 2D in the name and
now use the new package name.
9-2
Old Name
New Name
video.Autocorrelator2D
vision.Autocorrelator
video.Convolver2D
vision.Convolver
video.Crosscorrelator2D
vision.Crosscorrelator
video.DCT2D
vision.DCT
video.FFT2D
vision.FFT
video.Histogram2D
vision.Histogram
video.IDCT2D
vision.IDCT
video.IFFT2D
vision.IFFT
video.MedianFilter2D
vision.MedianFilter
New Computer Vision Functions
Extract Features
The extractFeatures function extracts feature vectors, also known as descriptors, from an
image.
Feature Matching
The matchFeatures function takes a pair of feature vectors, as returned by the
extractFeatures function, and finds the features which are most likely to correspond.
Uncalibrated Stereo Rectification
The estimateUncalibratedRectification function returns projective transformations for
rectifying stereo images.
Determine if Image Contains Epipole
The isEpipoleInImage function determines whether an image contains an epipole. This
function supports the estimateUncalibratedRectification function.
Epipolar Lines for Stereo Images
The epipolarLine computes epipolar lines for stereo images.
Line-to-Border Intersection Points
The lineToBorderPoints function calculates the location of the point of intersection of line
in an image with the image border. This function supports the epipolarLine function.
New Foreground Detector System Object
The vision.ForegroundDetector object computes a foreground mask using Gaussian
mixture models (GMM).
New Tracking Cars Using Gaussian Mixture Models Demo
The new Tracking Cars Using Gaussian Mixture Models demo illustrates the use of
Gaussian mixture models for detection and tracking of cars. The algorithm detects and
tracks the cars in a video by separating them from their background.
9-3
R2011a
Expanded To Video Display Block with Additional Video Formats
The To Video Display block now supports 4:2:2 YCbCr video input format.
New Printing Capability for the mplay Function and Video Viewer Block
You can now print the display information from the GUI interface of the mplay function
and the Video Viewer block.
Improved Display Updates for mplay Function, Video Viewer Block and
vision.VideoPlayer System Object
R2011a introduces the capability to improve the performance of mplay, the Video Viewer
block and the vision.VideoPlayer System object by reducing the frequency with which the
display updates. You can now choose between this new enhanced performance mode and
the old behavior. By default, all scopes operate in the new enhanced performance mode.
Improved Performance of FFT Implementation with FFTW library
The 2-D FFT, 2-D IFFT blocks include the use of the FFTW library.
Variable Size Data Support
The Resize block now supports variable size data. See Working with Variable-Size
Signals for more information about variable size data.
System Object Input and Property Warnings Changed to Errors
When a System object is locked (e.g., after the step method has been called), the
following situations now produce an error. This change prevents the loss of state
information.
• Changing the input data type
• Changing the number of input dimensions
• Changing the input complexity from real to complex
• Changing the data type, dimension, or complexity of tunable property
• Changing the value of a nontunable property
9-4
Compatibility Considerations
Previously, the object issued a warning for these situations. The object then unlocked,
reset its state information, relocked, and continued processing. To update existing code
so that it does not error, use the release method before changing any of the items listed
above.
System Object Code Generation Support
The following System objects now support code generation:
• vision.GeometricScaler
• vision.ForegroundDetector
MATLAB Compiler Support for System Objects
The Computer Vision System Toolbox supports the MATLAB Compiler for all objects
except vision.VideoPlayer. With this capability, you can use the MATLAB Compiler
to take MATLAB files, which can include System objects, as input and generate
standalone applications.
R2010a MAT Files with System Objects Load Incorrectly
If you saved a System object to a MAT file in R2010a and load that file in R2011a,
MATLAB may display a warning that the constructor must preserve the class of the
returned object. This occurs because an aspect of the class definition changed for that
object in R2011a. The object's saved property settings may not restore correctly.
Compatibility Considerations
MAT files containing a System object saved in R2010a may not load correctly in R2011a.
You should recreate the object with the desired property values and save the MAT file.
Documentation Examples Renamed
In previous releases, the examples used throughout the Video and Image Processing
Blockset™ documentation were named with a doc_ prefix. In R2011a, this changed to a
ex_ prefix. For example, in R2010b, you could launch an example model using the Video
9-5
R2011a
Viewer block by typing doc_thresholding at the MATLAB command line. To launch
the same model in R2011a, you must type ex_thresholding at the command line.
Compatibility Considerations
You can no longer launch Video and Image Processing Blockset™ documentation
example models using the doc_ prefix name. To open these models in R2011a, you must
replace the doc_ prefix in the model name with ex_.
9-6
R2010b
Version: 3.1
New Features
Bug Fixes
Compatibility Considerations
R2010b
New Estimate Fundamental Matrix Function for Describing Epipolar
Geometry
New Estimate Fundamental Matrix function for describing epipolar geometry. Epipolar
geometry applies to the geometry of stereo vision, where you can calculate depth
information based on corresponding points in stereo image pairs. The function supports
the generation of embeddable C code.
New Histogram System Object Replaces Histogram2D Object
The new video.Histogram System object replaces the video.Histogram2D System
object. The name change was made to align this object with its corresponding block.
Compatibility Considerations
The video.Histogram2D System object now issues a warning. Update code that uses
the 2D-Histogram object to use the new Histogram object.
New System Object release Method Replaces close Method
The close method has been replaced by the new release method, which unlocks the
object and releases memory and other resources, including files, used by the object. The
new release method includes the functionality of the old close method, which only
closed files used by the object.
Compatability Considerations
The close method now issues a warning. Update code that uses the close method to
use the new release method.
Expanded Embedded MATLAB Support
Embedded MATLAB® now supports the generation of embeddable C code for two
Image Processing Toolbox functions and additional Video and Image Processing
Blockset System objects. The generated C code meets the strict memory and data type
requirements of embedded target environments. Video and Image Processing Blockset
provides Embedded MATLAB support for these Image Processing Toolbox functions. See
Code Generation for details, including limitations.
10-2
Supported Image Processing Toolbox Functions
label2rgb
fspecial
Supported System objects
Video and Image Processing Blockset objects now support code generation:
video.CornerDetector
video.GeometricShearer
video.Histogram
video.MorpologicalBottomHat
video.MorpologicalTopHat
video.MultimediaFileReader
video.MultimediaFileWriter
Data Type Assistant and Ability to Specify Design Minimums and
Maximums Added to More Fixed-Point Blocks
The following blocks now offer a Data Type Assistant to help you specify fixed-point
data types on the block mask. Additionally, you can now enable simulation range
checking for certain data types on these blocks. To do so, specify appropriate minimum
and maximum values on the block dialog box. The blocks that support these features are:
• 2-D DCT
• 2-D FFT
• 2-D IDCT
• 2-D IFFT
• 2-D FIR Filter
For more information on these features, see the following sections in the Simulink
documentation:
• Using the Data Type Assistant
• Signal Ranges
10-3
R2010b
Data Types Pane Replaces the Data Type Attributes and Fixed-Point Panes
on Fixed-Point Blocks
In previous releases, some fixed-point blocks had a Data type attributes pane, and
others had a Fixed-point pane. The functionality of these panes remains the same,
but the pane now appears as the Data Types pane on all fixed-point Computer Vision
System Toolbox blocks.
Enhanced Fixed-Point and Integer Data Type Support with System Objects
For nonfloating point input, System objects now output the data type you specify.
Previously, the output was always a fixed-point, numeric fi object.
Compatability Considerations
Update any code that takes nonfloating point input, where you expect the object to
output a fi object.
Variable Size Data Support
Several Video and Image Processing Blockset blocks now support changes in signal size
during simulation. The following blocks support variable size data as of this release:
PSNR
2-D Correlation
Median Filter
2-D Convolution
Block Processing
2-D Autocorrelation
Image Complement
Deinterlacing
Gamma Correction
See Working with Variable-Size Signals for more information about variable size data.
Limitations Removed from Video and Image Processing Blockset
Multimedia Blocks and Objects
Support for reading interleaved AVI data and reading AVI files larger than 2GB on
UNIX platforms. Previously, this was only possible on Windows platforms. The following
blocks and System objects have the limitation removed:
10-4
From Multimedia File block
video.MultimediaFileReader System object
Support for writing AVI files larger than 2GB on UNIX platforms, which was previously
only possible on Windows platforms. The following blocks and System objects have the
limitation removed:
To Multimedia File block
video.MultimediaFileWriter System object
10-5
R2010a
Version: 3.0
New Features
Bug Fixes
R2010a
New System Objects Provide Video and Image Processing Algorithms for
use in MATLAB
System Objects are algorithms that provide stream processing, fixed-point modeling,
and code generation capabilities for use in MATLAB programs. These new objects allow
you to use video and image processing algorithms in MATLAB, providing the same
parameters, numerics and performance as corresponding Video and Image Processing
Blockset blocks. System objects can also be used in Simulink models via the Embedded
MATLAB Function block.
Intel Integrated Performance Primitives Library Support Added to 2-D
Correlation, 2-D Convolution, and 2-D FIR Filter Blocks
The 2-D Correlation, 2-D Convolution, and 2-D FIR Filter blocks are now taking
advantage of SSE Intel instruction set and multi-core processor capabilities for double
and single data types.
Variable Size Data Support
Several Video and Image Processing Blockset blocks now support changes in signal size
during simulation. The following blocks support variable size data as of this release:
11-2
2-D FFT
Hough Transform
2-D FIR Filter
Image Data Type Conversion
Apply Geometric Transformation
Image Pad
Autothreshold
Insert Text
Bottom-hat
Label
Chroma Resampling
2-D Maximum
Closing
2-D Mean
Color Space Conversion
Compositing
2-D Minimum
Contrast Adjustment
Opening
Dilation
Rotate
Edge Detection
2-D Standard Deviation
Erosion
Template Matching
Estimate Geometric Transformation
To Video Display
Find Local Maxima
Top-hat
Frame Rate Display
2-D Variance
Gaussian Pyramid
Video Viewer
See Working with Variable-Size Signals for more information about variable size data.
Expanded From and To Multimedia File Blocks with Additional Video
Formats
The To Multimedia File and From Multimedia File blocks now support 4:2:2 YCbCr video
formats.
The To Multimedia File block now supports WMV, WMA, and WAV file formats on Windows
platforms. This block now supports broadcasting WMV and WMA streams over the network.
New Simulink Demos
The Video and Image Processing Blockset contain new and enhanced demos.
New Modeling a Video Processing System for an FPGA Target Demo
This demo uses the Video and Image Processing Blockset in conjunction with Simulink
HDL Coder™ to show a design workflow for generating Hardware Design Language
(HDL) code suitable for targeting video processing application on an FPGA. The demo
reviews how to design a system that can operate on hardware.
New System Object Demos
New Image Rectification Demo
This demo shows how to rectify two uncalibrated images where the camera intrinsics
are unknown. Rectification is a useful procedure in many computer vision applications.
For example, in stereo vision, it can be used to reduce a 2-D matching problem to a 1-D
search. This demo is a prerequisite for the Stereo Vision demo.
New Stereo Vision Demo
This demo computes the depth map between two rectified stereo images using block
matching, which is the standard algorithm for high-speed stereo vision in hardware
11-3
R2010a
systems. It further explores dynamic programming to improve accuracy, and image
pyramiding to improve speed.
New Video Stabilization Using Point Feature Matching
This demo uses a point feature matching approach for video stabilization, which does not
require knowledge of a feature or region of the image to track. The demo automatically
searches for the background plane in a video sequence, and uses its observed distortion to
correct for camera motion. This demo presents a more advanced algorithm in comparison
to the existing Video Stabilization demo in Simulink.
SAD Block Obsoleted
The new Template Matching block introduced in the previous release, supports Sum of
Absolute Differences (SAD) algorithm. Consequently, the SAD Block has been obsoleted.
11-4